Release Notes:
- Allow Anthropic custom models to override "temperature"
This also centralized the defaulting of "temperature" to be inside of
each model's `into_x` call instead of being sprinkled around the code.
Release Notes:
- Added a new `assistant.inline_alternatives` setting to configure
additional models that will be used to perform inline assists in
parallel.
---------
Co-authored-by: Nathan <nathan@zed.dev>
Co-authored-by: Roy <roy@anthropic.com>
Co-authored-by: Adam <wolffiex@anthropic.com>
This PR does a little bit of a touch-up on the copywriting on the
assistant config UI. I had friends reporting to me that some of the
writing could be clearer, and hopefully, this goes into that direction!
Release Notes:
- N/A
Release Notes:
- Added support for OpenAI o1-mini and o1-preview models.
---------
Co-authored-by: Jason Mancuso <7891333+jvmncs@users.noreply.github.com>
Co-authored-by: Bennet <bennet@zed.dev>
This is a barebones modification of the OpenAI provider code to
accommodate non-streaming completions. This is specifically for the o1
models, which do not support streaming. Tested that this is working by
running a `/workflow` with the following (arbitrarily chosen) settings:
```json
{
"language_models": {
"openai": {
"version": "1",
"available_models": [
{
"name": "o1-preview",
"display_name": "o1-preview",
"max_tokens": 128000,
"max_completion_tokens": 30000
},
{
"name": "o1-mini",
"display_name": "o1-mini",
"max_tokens": 128000,
"max_completion_tokens": 20000
}
]
}
},
}
```
Release Notes:
- Changed `low_speed_timeout_in_seconds` option to `600` for OpenAI
provider to accommodate recent o1 model release.
---------
Co-authored-by: Peter <peter@zed.dev>
Co-authored-by: Bennet <bennet@zed.dev>
Co-authored-by: Marshall Bowers <elliott.codes@gmail.com>
Add `/auto` behind a feature flag that's disabled for now, even for
staff.
We've decided on a different design for context inference, but there are
parts of /auto that will be useful for that, so we want them in the code
base even if they're unused for now.
Release Notes:
- N/A
---------
Co-authored-by: Antonio Scandurra <me@as-cii.com>
Co-authored-by: Marshall Bowers <elliott.codes@gmail.com>
This PR updates the message content for an LLM request to allow it
contain tool uses.
We need to send the tool uses back to the model in order for it to
recognize the subsequent tool results.
Release Notes:
- N/A
This PR makes it so we propagate the `stop_reason` from Anthropic up to
the Assistant so that we can take action based on it.
The `extract_content_from_events` function was moved from `anthropic` to
the `anthropic` module in `language_model` since it is more useful if it
is able to name the `LanguageModelCompletionEvent` type, as otherwise
we'd need an additional layer of plumbing.
Release Notes:
- N/A
This PR adjusts the approach we use to encoding tool uses in the
completion response to use a structured format rather than simply
injecting it into the response stream as text.
In #17170 we would encode the tool uses as XML and insert them as text.
This would require then re-parsing the tool uses out of the buffer in
order to use them.
The approach taken in this PR is to make `stream_completion` return a
stream of `LanguageModelCompletionEvent`s. Each of these events can be
either text, or a tool use.
A new `stream_completion_text` method has been added to `LanguageModel`
for scenarios where we only care about textual content (currently,
everywhere that isn't the Assistant context editor).
Release Notes:
- N/A
This PR updates the Assistant with support for receiving tool uses from
Anthropic models and capturing them as text in the context editor.
This is just laying the foundation for tool use. We don't yet fulfill
the tool uses yet, or define any tools for the model to use.
Here's an example of what it looks like using the example `get_weather`
tool from the Anthropic docs:
<img width="644" alt="Screenshot 2024-08-30 at 1 51 13 PM"
src="https://github.com/user-attachments/assets/3614f953-0689-423c-8955-b146729ea638">
Release Notes:
- N/A
This PR splits the `Content` type for Anthropic into two new types:
`RequestContent` and `ResponseContent`.
As I was going through the Anthropic API docs it seems that there are
different types of content that can be sent in requests vs what can be
returned in responses.
Using a separate type for each case tells the story a bit better and
makes it easier to understand, IMO.
Release Notes:
- N/A
This PR makes it so the model's cache configuration gets passed through
from the base model when using the Zed provider.
Release Notes:
- Fixed caching for Anthropic models when using the Zed provider.
### Pull Request Title
Introduce `max_output_tokens` Field for OpenAI Models
https://platform.deepseek.com/api-docs/news/news0725/#4-8k-max_tokens-betarelease-longer-possibilities
### Description
This commit introduces a new field `max_output_tokens` to the OpenAI
models, which allows specifying the maximum number of tokens that can be
generated in the output. This field is now integrated into the request
handling across multiple crates, ensuring that the output token limit is
respected during language model completions.
Changes include:
- Adding `max_output_tokens` to the `Custom` variant of the
`open_ai::Model` enum.
- Updating the `into_open_ai` method in `LanguageModelRequest` to accept
and use `max_output_tokens`.
- Modifying the `OpenAiLanguageModel` and `CloudLanguageModel`
implementations to pass `max_output_tokens` when converting requests.
- Ensuring that the `max_output_tokens` field is correctly serialized
and deserialized in relevant structures.
This enhancement provides more control over the output length of OpenAI
model responses, improving the flexibility and accuracy of language
model interactions.
### Changes
- Added `max_output_tokens` to the `Custom` variant of the
`open_ai::Model` enum.
- Updated the `into_open_ai` method in `LanguageModelRequest` to accept
and use `max_output_tokens`.
- Modified the `OpenAiLanguageModel` and `CloudLanguageModel`
implementations to pass `max_output_tokens` when converting requests.
- Ensured that the `max_output_tokens` field is correctly serialized and
deserialized in relevant structures.
### Related Issue
https://github.com/zed-industries/zed/pull/16358
### Screenshots / Media
N/A
### Checklist
- [x] Code compiles correctly.
- [x] All tests pass.
- [ ] Documentation has been updated accordingly.
- [ ] Additional tests have been added to cover new functionality.
- [ ] Relevant documentation has been updated or added.
### Release Notes
- Added `max_output_tokens` field to OpenAI models for controlling
output token length.
This makes it easier to debug why resetting a key doesn't work. We now
show when the key is set via an env var and if so, we disable the
reset-key button and instead give instructions.
Release Notes:
- N/A
Co-authored-by: Bennet <bennet@zed.dev>
This commit adds a custom icon for Anthropic hosted models.
- Adding a new SVG icon for Anthropic hosted models.
- The new icon is located at: `assets/icons/ai_anthropic_hosted.svg`
- Updating the LanguageModel trait to include an optional icon method
- Implementing the icon method for CloudModel to return the custom icon
for Anthropic hosted models
- Updating the UI components to use the model-specific icon when
available
- Adding a new IconName variant for the Anthropic hosted icon
We should change the non-hosted icon in some small way to distinguish it
from the hosted version. I duplicated the path for now so we can
hopefully add it for the next release.
Release Notes:
- N/A
Release Notes:
- Adds support for Prompt Caching in Anthropic. For models that support
it this can dramatically lower cost while improving performance.
This PR is just a refactor, to pave the way toward adding a view for
workflow step resolution. The entity carries the state of the tool
call's streaming output.
Release Notes:
- N/A
This PR is a refactor to pave the way for allowing the user to view and
edit workflow step resolutions. I've made tool calls work more like
normal streaming completions for all providers. The `use_any_tool`
method returns a stream of strings (which contain chunks of JSON). I've
also done some minor cleanup of language model providers in general,
removing the duplication around handling streaming responses.
Release Notes:
- N/A
For future reference: WIP branch of copy/pasting a mixture of images and
text: https://github.com/zed-industries/zed/tree/copy-paste-images -
we'll come back to that one after landing this one.
Release Notes:
- You can now paste images into the Assistant Panel to include them as
context. Currently works only on Mac, and with Anthropic models. Future
support is planned for more models, operating systems, and image
clipboard operations.
---------
Co-authored-by: Antonio <antonio@zed.dev>
Co-authored-by: Mikayla <mikayla@zed.dev>
Co-authored-by: Jason <jason@zed.dev>
Co-authored-by: Kyle <kylek@zed.dev>
This PR adds feature-flagged access to the LLM service.
We've repurposed the `language-models` feature flag to be used for
providing access to Claude 3.5 Sonnet through the Zed provider.
The remaining RPC endpoints that were previously behind the
`language-models` feature flag are now behind a staff check.
We also put some Zed Pro related messaging behind a feature flag.
Release Notes:
- N/A
---------
Co-authored-by: Max <max@zed.dev>
Now, when an anthropic request is invalid or anthropic's API is down,
we'll expose that to the user instead of just returning a generic 500.
Release Notes:
- N/A
Co-authored-by: Marshall <marshall@zed.dev>
This PR makes it so hitting upstream rate limits from Anthropic result
in an HTTP 429 response instead of an HTTP 500.
To do this we need to surface structured errors out of the `anthropic`
crate.
Release Notes:
- N/A
This adds the requirement for users to accept the terms of service the
first time they send a message with the Cloud provider.
Once this is out and in a nightly, we need to add the check to the
server side too, to authenticate access to the models.
Demo:
https://github.com/user-attachments/assets/0edebf74-8120-4fa2-b801-bb76f04e8a17
Release Notes:
- N/A
This PR removes the `llm-service` feature flag and makes it so all
completions are done via the LLM service when using the Zed provider.
Release Notes:
- N/A
This PR polishes elements around setting up LLM providers on the
Assistant panel, including:
- [x] Adding banners for promoting Zed AI and to deal with the "No
provider set up" scenario
- [x] Tweaking the error popover whenever there's no API key added
- [ ] Making configuration panel scrollable
---
Release Notes:
- N/A
---------
Co-authored-by: Thorsten Ball <mrnugget@gmail.com>
Co-authored-by: Bennet Bo Fenner <53836821+bennetbo@users.noreply.github.com>
Co-authored-by: Marshall Bowers <1486634+maxdeviant@users.noreply.github.com>
- [x] OpenAI
- [ ] ~Google~ Moved into a separate branch at:
https://github.com/zed-industries/zed/tree/tool-calls-in-google-ai I've
ran into issues with having the API digest our schema without tripping
over itself - the function call parameters are malformed and whatnot. We
can resume from that branch if needed.
- [x] Ollama
- [x] Cloud
- [ ] ~Copilot Chat (?)~
Release Notes:
- Added tool calling capabilities to OpenAI and Ollama models.
